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Symmetry
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Advanced Symmetry Modelling and Services in Future IT Environments
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Advanced Symmetry Modelling and Services in Future IT Environments

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: closed (30 May 2015) | Viewed by 90899

Special Issue Editor

Prof. Dr. Neil Y. Yen

E-Mail Website
Guest Editor
System Intelligence Laboratory, Division of Computer Science, School of Computer Science and Engineering, The University of Aizu, Aizu, Japan
Interests: hybrid intelligence for information retrieval, management and optimization; awareness systems for human-centered support and social network analysis; computational intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advent of innovation on computing power and networking has changed human lives over the last decade. This information technology (IT) has evolved into a form of converged IT, such as ubiquitous computing, Internet of things, cloud computing, security and trust computing, human computer interface, intelligent transport system, etc. In the near future, it will be developed into the environment of Human-centric IT, and symmetry applications and services are required in the future IT environments that consider in the real-world and cyber-world. In this special issue, we will discuss symmetry modelling and services that are indispensably considered in future IT environments.

This special issue aims to provide an advanced theory and application for researchers and practitioners to contribute original research and review articles that present state-of-the-art research outcomes, practical results, and the latest findings in advanced symmetry modelling and services in future IT environments.

Prof. Dr. Neil Y. Yen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


Keywords

  • symmetry modelling for future it environments (fite)
  • symmetry applications for fite
  • symmetry services for fite
  • symmetry in ubiquitous computing
  • symmetry in internet of things
  • symmetry in cloud computing
  • symmetry in security and trust computing
  • symmetry in human centric computing
  • symmetry in intelligent transport system

Published Papers (14 papers)

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Research

2250 KiB  
Article
New Security Development and Trends to Secure the SCADA Sensors Automated Transmission during Critical Sessions
by Aamir Shahzad, Malrey Lee, Hyung Doo Kim, Seon-mi Woo and Naixue Xiong
Symmetry 2015, 7(4), 1945-1980; https://doi.org/10.3390/sym7041945 - 23 Oct 2015
Cited by 17 | Viewed by 7819
Abstract
Modern technology enhancements have been used worldwide to fulfill the requirements of the industrial sector, especially in supervisory control and data acquisition (SCADA) systems as a part of industrial control systems (ICS). SCADA systems have gained popularity in industrial automations due to technology [...] Read more.
Modern technology enhancements have been used worldwide to fulfill the requirements of the industrial sector, especially in supervisory control and data acquisition (SCADA) systems as a part of industrial control systems (ICS). SCADA systems have gained popularity in industrial automations due to technology enhancements and connectivity with modern computer networks and/or protocols. The procurement of new technologies has made SCADA systems important and helpful to processing in oil lines, water treatment plants, and electricity generation and control stations. On the other hand, these systems have vulnerabilities like other traditional computer networks (or systems), especially when interconnected with open platforms. Many international organizations and researchers have proposed and deployed solutions for SCADA security enhancement, but most of these have been based on node-to-node security, without emphasizing critical sessions that are linked directly with industrial processing and automation. This study concerns SCADA security measures related to critical processing with specified sessions of automated polling, analyzing cryptography mechanisms and deploying the appropriate explicit inclusive security solution in a distributed network protocol version 3 (DNP3) stack, as part of a SCADA system. The bytes flow through the DNP3 stack with security computational bytes within specified critical intervals defined for polling. We took critical processing knowledge into account when designing a SCADA/DNP3 testbed and deploying a cryptography solution that did not affect communications. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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1575 KiB  
Article
Development of Network Analysis and Visualization System for KEGG Pathways
by Dongmin Seo, Min-Ho Lee and Seok Jong Yu
Symmetry 2015, 7(3), 1275-1288; https://doi.org/10.3390/sym7031275 - 16 Jul 2015
Cited by 6 | Viewed by 6363
Abstract
Big data refers to informationalization technology for extracting valuable information through the use and analysis of large-scale data and, based on that data, deriving plans for response or predicting changes. With the development of software and devices for next generation sequencing, a vast [...] Read more.
Big data refers to informationalization technology for extracting valuable information through the use and analysis of large-scale data and, based on that data, deriving plans for response or predicting changes. With the development of software and devices for next generation sequencing, a vast amount of bioinformatics data has been generated recently. Also, bioinformatics data based big-data technology is rising rapidly as a core technology by the bioinformatician, biologist and big-data scientist. KEGG pathway is bioinformatics data for understanding high-level functions and utilities of the biological system. However, KEGG pathway analysis requires a lot of time and effort because KEGG pathways are high volume and very diverse. In this paper, we proposed a network analysis and visualization system that crawl user interest KEGG pathways, construct a pathway network based on a hierarchy structure of pathways and visualize relations and interactions of pathways by clustering and selecting core pathways from the network. Finally, we construct a pathway network collected by starting with an Alzheimer’s disease pathway and show the results on clustering and selecting core pathways from the pathway network. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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466 KiB  
Article
Hierarchical Clustering Using One-Class Support Vector Machines
by Gyemin Lee
Symmetry 2015, 7(3), 1164-1175; https://doi.org/10.3390/sym7031164 - 01 Jul 2015
Cited by 2 | Viewed by 5731
Abstract
This paper presents a novel hierarchical clustering method using support vector machines. A common approach for hierarchical clustering is to use distance for the task. However, different choices for computing inter-cluster distances often lead to fairly distinct clustering outcomes, causing interpretation difficulties in [...] Read more.
This paper presents a novel hierarchical clustering method using support vector machines. A common approach for hierarchical clustering is to use distance for the task. However, different choices for computing inter-cluster distances often lead to fairly distinct clustering outcomes, causing interpretation difficulties in practice. In this paper, we propose to use a one-class support vector machine (OC-SVM) to directly find high-density regions of data. Our algorithm generates nested set estimates using the OC-SVM and exploits the hierarchical structure of the estimated sets. We demonstrate the proposed algorithm on synthetic datasets. The cluster hierarchy is visualized with dendrograms and spanning trees. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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1459 KiB  
Article
Multiple Minimum Support-Based Rare Graph Pattern Mining Considering Symmetry Feature-Based Growth Technique and the Differing Importance of Graph Elements
by Gangin Lee, Unil Yun, Heungmo Ryang and Donggyu Kim
Symmetry 2015, 7(3), 1151-1163; https://doi.org/10.3390/sym7031151 - 26 Jun 2015
Cited by 11 | Viewed by 5237
Abstract
Frequent graph pattern mining is one of the most interesting areas in data mining, and many researchers have developed a variety of approaches by suggesting efficient, useful mining techniques by integration of fundamental graph mining with other advanced mining works. However, previous graph [...] Read more.
Frequent graph pattern mining is one of the most interesting areas in data mining, and many researchers have developed a variety of approaches by suggesting efficient, useful mining techniques by integration of fundamental graph mining with other advanced mining works. However, previous graph mining approaches have faced fatal problems that cannot consider important characteristics in the real world because they cannot process both (1) different element importance and (2) multiple minimum support thresholds suitable for each graph element. In other words, graph elements in the real world have not only frequency factors but also their own importance; in addition, various elements composing graphs may require different thresholds according to their characteristics. However, traditional ones do not consider such features. To overcome these issues, we propose a new frequent graph pattern mining method, which can deal with both different element importance and multiple minimum support thresholds. Through the devised algorithm, we can obtain more meaningful graph pattern results with higher importance. We also demonstrate that the proposed algorithm has more outstanding performance compared to previous state-of-the-art approaches in terms of graph pattern generation, runtime, and memory usage. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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845 KiB  
Article
Kinematic Skeleton Based Control of a Virtual Simulator for Military Training
by Soyeon Lee, Sangjoon Park, Kyoil Chung and Choongho Cho
Symmetry 2015, 7(2), 1043-1060; https://doi.org/10.3390/sym7021043 - 11 Jun 2015
Cited by 5 | Viewed by 5595
Abstract
Virtual simulation technology has been considered as a highly efficient and cost-effective solution for a soldier training system, and evolved into diverse combinations of hardware and software. To maximize the virtual reality effect within a restricted space, a locomotion interface such as an [...] Read more.
Virtual simulation technology has been considered as a highly efficient and cost-effective solution for a soldier training system, and evolved into diverse combinations of hardware and software. To maximize the virtual reality effect within a restricted space, a locomotion interface such as an omni-directional treadmill is introduced as a major component of a virtual simulator, therefore real time interaction between human and the virtual simulator becomes very important. Displacement and heading changes of the trainee are crucial information to control the virtual simulator when we implement highly reactive motion control for the omni-directional treadmill and interaction control of the virtual contents. This paper proposes a control parameter estimation algorithm for the virtual training simulator by using two types of motion capture sensors and presents the experimental results. Kinematic joint positions are analyzed to estimate the trainee’s location and velocity for feedback and feedforward control of the omni-directional treadmill. The accuracy of two approaches is evaluated by comparing with the reference system, which gives a ground truth value. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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647 KiB  
Article
Development of Patient Status-Based Dynamic Access System for Medical Information Systems
by Chang Won Jeong, Vathana Ban, Kwon Ha Yoon and Su Chong Joo
Symmetry 2015, 7(2), 1028-1039; https://doi.org/10.3390/sym7021028 - 08 Jun 2015
Cited by 1 | Viewed by 5681
Abstract
Recently, the hospital information system environment using IT communication technology and utilization of medical information has been increasing. In the medical field, the medical information system only supports the transfer of patient information to medical staff through an electronic health record, without information [...] Read more.
Recently, the hospital information system environment using IT communication technology and utilization of medical information has been increasing. In the medical field, the medical information system only supports the transfer of patient information to medical staff through an electronic health record, without information about patient status. Hence, it needs a method of real-time monitoring for the patient. Also, in this environment, a secure method in approaching healthcare through various smart devices is required. Therefore, in this paper, in order to classify the status of the patients, we propose a dynamic approach of the medical information system in a hospital information environment using the dynamic access control method. Also, we applied the symmetric method of AES (Advanced Encryption Standard). This was the best encryption algorithm for sending and receiving biological information. We can define usefulness as the dynamic access application service based on the final result of the proposed system. The proposed system is expected to provide a new solution for a convenient medical information system. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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586 KiB  
Article
Secure Cooperative Spectrum Sensing via a Novel User-Classification Scheme in Cognitive Radios for Future Communication Technologies
by Muhammad Usman and Koo Insoo
Symmetry 2015, 7(2), 675-688; https://doi.org/10.3390/sym7020675 - 14 May 2015
Cited by 5 | Viewed by 5018
Abstract
Future communication networks would be required to deliver data on a far greater scale than is known to us today, thus mandating the maximal utilization of the available radio spectrum using cognitive radios. In this paper, we have proposed a novel cooperative spectrum [...] Read more.
Future communication networks would be required to deliver data on a far greater scale than is known to us today, thus mandating the maximal utilization of the available radio spectrum using cognitive radios. In this paper, we have proposed a novel cooperative spectrum sensing approach for cognitive radios. In cooperative spectrum sensing, the fusion center relies on reports of the cognitive users to make a global decision. The global decision is obtained by assigning weights to the reports received from cognitive users. Computation of such weights requires prior information of the probability of detection and the probability of false alarms, which are not readily available in real scenarios. Further, the cognitive users are divided into reliable and unreliable categories based on their weighted energy by using some empirical threshold. In this paper, we propose a method to classify the cognitive users into reliable, neutral and unreliable categories without using any pre-defined or empirically-obtained threshold. Moreover, the computation of weights does not require the detection, or false alarm probabilities, or an estimate of these probabilities. Reliable cognitive users are assigned the highest weights; neutral cognitive users are assigned medium weights (less than the reliable and higher than the unreliable cognitive users’ weights); and unreliable users are assigned the least weights. We show the performance improvement of our proposed method through simulations by comparing it with the conventional cooperative spectrum sensing scheme through different metrics, like receiver operating characteristic (ROC) curve and mean square error. For clarity, we also show the effect of malicious users on detection probability and false alarm probability individually through simulations. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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20497 KiB  
Article
Online Social Snapshots of a Generic Facebook Session Based on Digital Insight Data for a Secure Future IT Environment
by Hai-Cheng Chu and Jong Hyuk Park
Symmetry 2015, 7(2), 546-560; https://doi.org/10.3390/sym7020546 - 04 May 2015
Viewed by 4973
Abstract
Physical memory acquisition has been an import facet for digital forensics (DF) specialists due to its volatile characteristics. Nowadays, thousands of millions of global participants utilize online social networking (OSN) mechanisms to expand their social lives, ranging from business-oriented purposes to leisure motivations. [...] Read more.
Physical memory acquisition has been an import facet for digital forensics (DF) specialists due to its volatile characteristics. Nowadays, thousands of millions of global participants utilize online social networking (OSN) mechanisms to expand their social lives, ranging from business-oriented purposes to leisure motivations. Facebook (FB) is one of the most dominant social networking sites (SNS) available today. Unfortunately, it has been a major avenue for cybercriminals to commit illegal activities. Therefore, the digital traces of previous sessions of an FB user play an essential role as the first step for DF experts to pursue the disclosure of the identity of the suspect who was exploiting FB. In this research work, we provide a systematic methodology to reveal a previous session of an FB identity, as well as his/her partial social circle via collecting, analyzing, preserving and presenting the associated digital traces to obtain the online social snapshots of a specific FB user who was utilizing a computing device with Internet Explorer (IE) 10 without turning off the power of the gadget. This novel approach can be a paradigm for how DF specialists ponder the crime scene to conduct the first response in order to avoid the permanent loss of the precious digital evidence in previous FB sessions. The hash values of the image files of the random access memory (RAM) of the computing device have proven to be identical before and after forensics operations, which could be probative evidence in a court of law. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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592 KiB  
Article
Provable Fair Document Exchange Protocol with Transaction Privacy for E-Commerce
by Ren-Junn Hwang and Chih-Hua Lai
Symmetry 2015, 7(2), 464-487; https://doi.org/10.3390/sym7020464 - 28 Apr 2015
Cited by 10 | Viewed by 5051
Abstract
Transaction privacy has attracted a lot of attention in the e-commerce. This study proposes an efficient and provable fair document exchange protocol with transaction privacy. Using the proposed protocol, any untrusted parties can fairly exchange documents without the assistance of online, trusted third [...] Read more.
Transaction privacy has attracted a lot of attention in the e-commerce. This study proposes an efficient and provable fair document exchange protocol with transaction privacy. Using the proposed protocol, any untrusted parties can fairly exchange documents without the assistance of online, trusted third parties. Moreover, a notary only notarizes each document once. The authorized document owner can exchange a notarized document with different parties repeatedly without disclosing the origin of the document or the identities of transaction participants. Security and performance analyses indicate that the proposed protocol not only provides strong fairness, non-repudiation of origin, non-repudiation of receipt, and message confidentiality, but also enhances forward secrecy, transaction privacy, and authorized exchange. The proposed protocol is more efficient than other works. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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13777 KiB  
Article
A Development of Hybrid Drug Information System Using Image Recognition
by HwaMin Lee, Doo-Soon Park and Min-Hyung Choi
Symmetry 2015, 7(2), 376-382; https://doi.org/10.3390/sym7020376 - 16 Apr 2015
Viewed by 4926
Abstract
In order to prevent drug abuse or misuse cases and avoid over-prescriptions, it is necessary for medicine taker to be provided with detailed information about the medicine. In this paper, we propose a drug information system and develop an application to provide information [...] Read more.
In order to prevent drug abuse or misuse cases and avoid over-prescriptions, it is necessary for medicine taker to be provided with detailed information about the medicine. In this paper, we propose a drug information system and develop an application to provide information through drug image recognition using a smartphone. We designed a contents-based drug image search algorithm using the color, shape and imprint of drug. Our convenient application can provide users with detailed information about drugs and prevent drug misuse. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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477 KiB  
Article
Live Mobile Distance Learning System for Smart Devices
by Jang Ho Lee, Doo-Soon Park, Young-Sik Jeong and Jong Hyuk Park
Symmetry 2015, 7(2), 294-304; https://doi.org/10.3390/sym7020294 - 25 Mar 2015
Cited by 2 | Viewed by 4864
Abstract
In recent years, mobile and ubiquitous computing has emerged in our daily lives, and extensive studies have been conducted in various areas using smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, in order to realize this computing [...] Read more.
In recent years, mobile and ubiquitous computing has emerged in our daily lives, and extensive studies have been conducted in various areas using smart devices, such as tablets, smartphones, smart TVs, smart refrigerators, and smart media devices, in order to realize this computing technology. Especially, the integration of mobile networking technology and intelligent mobile devices has made it possible to develop the advanced mobile distance learning system that supports portable smart devices such as smartphones and tablets for the future IT environment. We present a synchronous mobile learning system that enables both instructor and student to participate in distance learning with their tablets. When an instructor gives a lecture using a tablet with front-face camera by bringing up slides and making annotations on them, students in the distance can watch the instructor and those slides with annotation on their own tablets in real time. A student can also ask a question or have a discussion together using the text chat feature of the system during a learning session. We also show the user evaluation of the system. A user survey shows that about 67% are in favor of the prototype of the system. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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676 KiB  
Article
Teaching-Learning Activity Modeling Based on Data Analysis
by Kyungrog Kim, Yoo-Joo Choi, Mihui Kim, Jung-Won Lee, Doo-Soon Park and Nammee Moon
Symmetry 2015, 7(1), 206-219; https://doi.org/10.3390/sym7010206 - 05 Mar 2015
Cited by 6 | Viewed by 6048
Abstract
Numerous studies are currently being carried out on personalized services based on data analysis to find and provide valuable information about information overload. Furthermore, the number of studies on data analysis of teaching-learning activities for personalized services in the field of teaching-learning is [...] Read more.
Numerous studies are currently being carried out on personalized services based on data analysis to find and provide valuable information about information overload. Furthermore, the number of studies on data analysis of teaching-learning activities for personalized services in the field of teaching-learning is increasing, too. This paper proposes a learning style recency-frequency-durability (LS-RFD) model for quantified analysis on the level of activities of learners, to provide the elements of teaching-learning activities according to the learning style of the learner among various parameters for personalized service. This is to measure preferences as to teaching-learning activity according to recency, frequency and durability of such activities. Based on the results, user characteristics can be classified into groups for teaching-learning activity by categorizing the level of preference and activity of the learner. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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27304 KiB  
Article
Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts
by Jaewoon Lee, Yeonjin Kim, Myeong-Hyeon Heo, Dongho Kim and Byeong-Seok Shin
Symmetry 2015, 7(1), 182-192; https://doi.org/10.3390/sym7010182 - 27 Feb 2015
Cited by 19 | Viewed by 17817
Abstract
This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors [...] Read more.
This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors or the surface of actor’s costumes; the silhouette transforms its own shape frequently. To realize this work, we implemented a special projection system based on the real-time masking technique, that is to say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical. In live performance, using projection-based augmented reality technology enhances technical and theatrical aspects which were not possible with existing video projection techniques. The projected images on the surfaces of actor’s costume could not only express the particular scene of a performance more effectively, but also lead the audience to an extraordinary visual experience. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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550 KiB  
Article
Output Effect Evaluation Based on Input Features in Neural Incremental Attribute Learning for Better Classification Performance
by Ting Wang, Sheng-Uei Guan, Ka Lok Man, Jong Hyuk Park and Hui-Huang Hsu
Symmetry 2015, 7(1), 53-66; https://doi.org/10.3390/sym7010053 - 14 Jan 2015
Cited by 1 | Viewed by 4950
Abstract
Machine learning is a very important approach to pattern classification. This paper provides a better insight into Incremental Attribute Learning (IAL) with further analysis as to why it can exhibit better performance than conventional batch training. IAL is a novel supervised machine learning [...] Read more.
Machine learning is a very important approach to pattern classification. This paper provides a better insight into Incremental Attribute Learning (IAL) with further analysis as to why it can exhibit better performance than conventional batch training. IAL is a novel supervised machine learning strategy, which gradually trains features in one or more chunks. Previous research showed that IAL can obtain lower classification error rates than a conventional batch training approach. Yet the reason for that is still not very clear. In this study, the feasibility of IAL is verified by mathematical approaches. Moreover, experimental results derived by IAL neural networks on benchmarks also confirm the mathematical validation. Full article
(This article belongs to the Special Issue Advanced Symmetry Modelling and Services in Future IT Environments)
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